Genomic selection can be implemented based on the genomic relationship matrix (GBLUP) and can be combined with phenotypes from nongenotyped animals through the use of best linear unbiased prediction (BLUP). A common method to combine both sources of information involves multiple steps, but is difficult to use with complicated models and is nonoptimal. A simpler method, termed single-step GBLUP, or ssGBLUP, integrates the genomically derived relationships (G) with population-based pedigree relationships (A) into a combined relationship matrix (H) and allows for genomic selection in a single step. The ssGBLUP method is easy to implement and uses standard BLUP-based programs. Experiences with field data in chickens, pigs, and dairy indicate that ssGBLUP is more accurate yet much simpler than multi-step methods. The current limits of ssGBLUP are approximately 100,000 genotypes and 18 traits. Models involving 10 million animals have been run successfully. The inverse of H can also be used in existing programs for parameter estimationm, but a properly scaled G is needed for unbiased estimation. Also, as genomic predictions can be converted to SNP effects, ssGBLUP is useful for genomic-wide association studies. The single-step method for genomic selection translates the use of genomic information into standard BLUP, and variance-component estimation programs become a routine.
%0 Journal Article
%1 Misztal01092013
%A Misztal, Ignacy
%A Aggrey, Samuel E.
%A Muir, William M.
%D 2013
%J Poultry Science
%K 2013 chicken genomics review
%N 9
%P 2530-2534
%R 10.3382/ps.2012-02739
%T Experiences with a single-step genome evaluation
%U http://ps.oxfordjournals.org/content/92/9/2530.abstract
%V 92
%X Genomic selection can be implemented based on the genomic relationship matrix (GBLUP) and can be combined with phenotypes from nongenotyped animals through the use of best linear unbiased prediction (BLUP). A common method to combine both sources of information involves multiple steps, but is difficult to use with complicated models and is nonoptimal. A simpler method, termed single-step GBLUP, or ssGBLUP, integrates the genomically derived relationships (G) with population-based pedigree relationships (A) into a combined relationship matrix (H) and allows for genomic selection in a single step. The ssGBLUP method is easy to implement and uses standard BLUP-based programs. Experiences with field data in chickens, pigs, and dairy indicate that ssGBLUP is more accurate yet much simpler than multi-step methods. The current limits of ssGBLUP are approximately 100,000 genotypes and 18 traits. Models involving 10 million animals have been run successfully. The inverse of H can also be used in existing programs for parameter estimationm, but a properly scaled G is needed for unbiased estimation. Also, as genomic predictions can be converted to SNP effects, ssGBLUP is useful for genomic-wide association studies. The single-step method for genomic selection translates the use of genomic information into standard BLUP, and variance-component estimation programs become a routine.
@article{Misztal01092013,
abstract = {Genomic selection can be implemented based on the genomic relationship matrix (GBLUP) and can be combined with phenotypes from nongenotyped animals through the use of best linear unbiased prediction (BLUP). A common method to combine both sources of information involves multiple steps, but is difficult to use with complicated models and is nonoptimal. A simpler method, termed single-step GBLUP, or ssGBLUP, integrates the genomically derived relationships (G) with population-based pedigree relationships (A) into a combined relationship matrix (H) and allows for genomic selection in a single step. The ssGBLUP method is easy to implement and uses standard BLUP-based programs. Experiences with field data in chickens, pigs, and dairy indicate that ssGBLUP is more accurate yet much simpler than multi-step methods. The current limits of ssGBLUP are approximately 100,000 genotypes and 18 traits. Models involving 10 million animals have been run successfully. The inverse of H can also be used in existing programs for parameter estimationm, but a properly scaled G is needed for unbiased estimation. Also, as genomic predictions can be converted to SNP effects, ssGBLUP is useful for genomic-wide association studies. The single-step method for genomic selection translates the use of genomic information into standard BLUP, and variance-component estimation programs become a routine.},
added-at = {2016-05-14T18:13:43.000+0200},
author = {Misztal, Ignacy and Aggrey, Samuel E. and Muir, William M.},
biburl = {https://www.bibsonomy.org/bibtex/23e47d421b744c5b2cfa06375b13d324d/uga.abgg},
doi = {10.3382/ps.2012-02739},
eprint = {http://ps.oxfordjournals.org/content/92/9/2530.full.pdf+html},
interhash = {6a0eb800176b4608cca5016951283360},
intrahash = {3e47d421b744c5b2cfa06375b13d324d},
journal = {Poultry Science},
keywords = {2013 chicken genomics review},
number = 9,
pages = {2530-2534},
timestamp = {2016-05-14T18:13:43.000+0200},
title = {Experiences with a single-step genome evaluation
},
url = {http://ps.oxfordjournals.org/content/92/9/2530.abstract},
volume = 92,
year = 2013
}